Feedback: Study Guide (Biology 4.4)

Why organisms need feedback

Your cells work best in a narrow range of conditions. Enzymes need a suitable temperature and pH. Cells need enough glucose, but not so much that water is drawn out of them by osmosis. Yet conditions change all the time: you eat, you fast, you exercise, the weather changes.

Homeostasis is keeping the internal environment close to a target, called the set point, despite these changes. It is dynamic: the value drifts away and is pulled back, again and again. The pulling back depends on feedback.

Parts of a feedback loop

Every feedback loop has the same parts:

1. A stimulus: a change in a variable, such as blood glucose rising.
2. A sensor (receptor) that detects the change.
3. A control centre that compares the value with the set point and sends a signal, often a hormone or a nerve impulse.
4. An effector, a cell or organ that carries out a response.
5. The response, which changes the variable.

The loop is called feedback because the response acts back on the stimulus. The key question is: in which direction?

	Negative feedback	Positive feedback
Effect of the response on the original change	reduces it	increases it
What happens to the variable	returns towards the set point	moves further from its starting value
Typical job	keeping conditions stable	completing an event quickly
How the loop stops	the stimulus shrinks as the variable returns	an outside event removes the stimulus

Negative feedback: returning to the set point

Blood glucose, an organism-level loop

After a meal, glucose from digested food enters the blood. β (beta) cells in the pancreas detect the rise and release the hormone insulin. Insulin binds receptors on muscle, fat and liver cells. In response, these cells take in more glucose, and the liver links glucose into glycogen for storage. Blood glucose falls. As it falls, the stimulus shrinks, so the β cells release less insulin. The loop switches itself down.

During fasting or exercise, glucose falls. α (alpha) cells in the pancreas release glucagon. Glucagon binds receptors on liver cells, which break glycogen down and release glucose into the blood. Glucose rises back, and glucagon release falls.

Both loops are negative feedback: the response opposes the change. Insulin and glucagon have opposite effects, so together they hold glucose in a narrow range. Each one is also a signal transduction pathway like those in Topic 4.3: hormone, receptor, relay, response.

Body temperature

If your body temperature rises, sensors in the skin and brain detect it. The brain triggers sweating and widening of blood vessels in the skin, which lose heat. Temperature falls back. If it drops, shivering (muscle activity releases heat) and narrowing of skin blood vessels (less heat lost) raise it again. The same logic applies: the response opposes the change.

Negative feedback inside cells

Negative feedback is not only for whole organisms. It also works at smaller scales.

• Molecular level: end-product inhibition. In a chain of enzyme reactions, A → B → C → D, the final product D can bind an allosteric site on the first enzyme and slow it down. When D builds up, less is made; when D is used up, the first enzyme speeds up again. The cell makes D only as fast as it needs it.
• Cellular level. A cell that already contains plenty of cholesterol makes less of the enzymes that synthesise it. Its own product turns down its own supply.

Positive feedback: amplifying a change

In positive feedback, the response adds to the stimulus. Each round makes the next round stronger, and the variable moves further and further from its starting value. This would be harmful for something like blood glucose, but it is useful when an event must be completed quickly and fully.

• Childbirth. The baby’s head presses on the cervix. Stretch receptors send nerve impulses to the brain, and the pituitary gland releases the hormone oxytocin. Oxytocin makes the muscle of the uterus contract more strongly. Stronger contractions push the baby harder against the cervix, which causes more oxytocin release, and so on. The loop ends with an outside event: the birth itself removes the pressure on the cervix.
• Lactation. A baby suckling stimulates nerve endings in the nipple. The mother releases more oxytocin (milk flows) and more prolactin (more milk is made). More feeding leads to more milk, which supports more feeding. When the baby stops feeding, the stimulus is removed and milk production falls.
• Fruit ripening. Ripening fruit releases the gas ethylene. Ethylene triggers ripening in the fruit’s own cells and in nearby fruit, and ripening cells release more ethylene. One ripe fruit can speed the ripening of a whole box.
• Blood clotting. Damaged tissue and platelets release chemicals that activate more platelets and clotting factors, which release more of those chemicals. A clot forms rapidly. It stops once the wound is sealed.

When feedback fails

Predicting the effect of a disruption is a core skill for this topic. Use three steps:

1. Find the broken link. Is the problem in the sensor, the signal, the receptor on the target cells or the effector?
2. Follow the loop. What can no longer happen? What does the variable do as a result?
3. Look for knock-on effects. If the variable stays away from the set point, the stimulus never goes away, so the control centre may keep signalling harder.

Diabetes mellitus shows two different broken links in the same loop:

	Broken link	Insulin in blood	Blood glucose
Type 1	the immune system destroys the β cells, so insulin is not made	very low	high, especially after meals
Type 2	target cells respond weakly to insulin (insulin resistance)	often normal or high, at least at first	high

In both, glucose stays above the set point. In type 2, the β cells keep detecting high glucose, so they keep releasing insulin. That is the knock-on effect of a loop that cannot close.

Worked example 1: reading glucose data to locate a fault

Question. Two adults, P and Q, each drink the same glucose solution after fasting overnight. Blood glucose is measured every 30 minutes. The data are fictional.

Time / min	0	30	60	90	120
P / mg dL⁻¹	88	140	122	100	90
Q / mg dL⁻¹	118	196	214	200	182

Tests show that Q’s insulin level is higher than P’s at every time point.

(a) Compare the size and timing of the peaks. (b) Compare how far each person has recovered by 120 minutes. (c) Identify the broken link in Q’s feedback loop and justify your answer. (d) Predict what would happen to Q’s glucose if Q’s β cells gradually stopped working.

(a) Peaks. P rises from 88 to a peak of 140 mg dL⁻¹ at 30 min, a rise of 52. Q rises from 118 to 214 mg dL⁻¹ at 60 min, a rise of 96. Q’s peak is higher, later and starts from a higher fasting value.

(b) Recovery. P falls from 140 to 90: 50 of the 52 mg dL⁻¹ rise is reversed (about 96%), and P ends only 2 mg dL⁻¹ (2.3%) above the start. Q falls only from 214 to 182: 32 of the 96 mg dL⁻¹ rise (about 33%). At 120 min Q is still 64 mg dL⁻¹, or 54%, above the starting value.

(c) Broken link. In Q, negative feedback is weak: glucose is not brought back towards the set point. The β cells are working, because insulin is high. So the signal is being sent but the target cells respond weakly to insulin: the fault is at the receptor or in the pathway inside the target cells. This pattern matches insulin resistance, the main fault in type 2 diabetes. The high insulin is the knock-on effect: glucose stays high, so the stimulus to the β cells never goes away.

(d) Prediction. With fewer working β cells, less insulin would be released. Target cells that already respond weakly would receive even less signal, so glucose would rise higher after a drink and stay high for longer, and fasting glucose would rise too.

Check. The units are the same throughout, and percentages use the starting value as the base. One test on two people cannot diagnose anything; the data only illustrate the reasoning.

Worked example 2: modelling how the two kinds of loop behave

Question. Use two simple models to compare the loops. (a) Negative feedback: a variable starts 40 units above its set point, and each round of the loop removes half of the remaining difference. Find the difference after 4 rounds. (b) Positive feedback: in a model of labour, the oxytocin level starts at 10 units and each contraction cycle increases it by 50%. How many cycles until it passes 100 units? (c) Predict the effect of a drug that blocks oxytocin receptors on the uterus.

(a) Each round multiplies the difference by 0.5: 40 → 20 → 10 → 5 → 2.5 units. The variable approaches the set point and the corrections get smaller each round, because the stimulus is shrinking.

(b) Each cycle multiplies the level by 1.5: 10 → 15 → 22.5 → 33.8 → 50.6 → 75.9 → 113.9. It passes 100 units after 6 cycles. The increases get larger each round, because each response strengthens the stimulus.

(c) If oxytocin cannot bind its receptors, uterine contractions do not strengthen, the pressure on the cervix does not increase and the loop cannot build up. Labour would slow or stop. This is why such drugs can be used to delay labour that starts too early. The reverse is also used: synthetic oxytocin can start or strengthen labour.

Interpretation. The shapes are the signatures to look for in data: a negative feedback curve levels off at the set point, while a positive feedback curve keeps accelerating until something outside the loop stops it. Real loops are not this regular; the models show the pattern only.

Common misconceptions

• “Negative feedback means something bad happens.” Negative means the response opposes the change. It is the main way the body stays healthy.
• “Positive feedback maintains homeostasis by itself.” Positive feedback moves a variable away from its starting value. It serves the body only because it ends, and normal control then returns.
• “Insulin and glucagon are enzymes that break down or build glucose.” They are hormones. They bind receptors on target cells, and the cells’ own enzymes do the work.
• “Glucagon is the same as glycogen.” Glucagon is a hormone; glycogen is the storage carbohydrate it causes the liver to break down.
• “The set point is a fixed value the body never leaves.” The value constantly moves around the set point; feedback keeps pulling it back.
• “In type 2 diabetes there is no insulin.” Often insulin is present, even high; the target cells respond weakly.
• “Feedback only happens in whole organisms.” End-product inhibition is negative feedback at the molecular level.

Where this leads

Next, Topic 4.5, Cell Cycle, looks at how cells divide. In Topic 4.6 you will see that the cell cycle is guarded by checkpoints and signals that work on the same feedback logic, and that cancer can follow when that control breaks. Test yourself now with the practice questions, then use the revision notes and the checklist to consolidate.